GPT-3.5 Turbo Instruct

openai/gpt-3.5-turbo-instruct

OpenAI· 4K ctx

API onlytool call quant: unknown

spread (output, p90 ÷ p10)

— too few providers

$2.00 – $2.00 · 2 providers · max÷min 1.0×

2 providers priced · 2 offerings

Including routers & resellers

Cheapest / median / spread use providers that serve the model on their own capacity: first-party lab, hyperscaler, inference host.

Provider classes in the stats:

Blended $/M assumptionsInput : output: 1Cache-hit share of input%

blended = 90.9% input × [(1 − 70% cache) × input + 70% cache × cache-read] + 9.1% × output + cache writes (30% of uncached input) where a write price is published

A provider that publishes no cache price is blended with cache share 0 (all input at the input price) and labelled “no cache price published” — never penalised against identical in/out prices.

Provider	Input	Output	Cache rd	Blended
Poe router / aggregator	$1.40	$1.80	—	$1.44no cache price published
Azure hyperscaler	$1.50	$2.00	—	$1.55no cache price published
Azure Cognitive Services hyperscaler	$1.50	$2.00	—	$1.55no cache price published
Kilo Gateway router / aggregator	$1.50	$2.00	—	$1.55no cache price published
OpenRouter router / aggregator	$1.50	$2.00	—	$1.55no cache price published

Connect

Provider (default: cheapest output among direct providers)

$2.00 /M · hyperscaler

opencode.json

{
  "provider": {
    "azure": {
      "npm": "@ai-sdk/azure",
      "models": {
        "gpt-3.5-turbo-instruct": {}
      }
    }
  }
}

Set AZURE_RESOURCE_NAME, AZURE_API_KEY in your environment. Generated — verify against the OpenCode docs.

Not enough history yet — the min/median/max sparkline fills in as the daily snapshot accumulates.

Data: models.dev (MIT), snapshot 2026-10-17. Prices are vendor-published; verify before purchase. Methodology.